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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 11 of 11 1 Learning with joint inference and latent linguistic structure in graphical models ... Naradowsky, Jason. - : Macquarie University, 2022 BASE Show details 2 Learning with joint inference and latent linguistic structure in graphical models ... Naradowsky, Jason. - : Macquarie University, 2022 BASE Show details 3 Rethinking Offensive Text Detection as a Multi-Hop Reasoning Problem ... Zhang, Qiang; Naradowsky, Jason; Miyao, Yusuke. - : arXiv, 2022 Abstract: We introduce the task of implicit offensive text detection in dialogues, where a statement may have either an offensive or non-offensive interpretation, depending on the listener and context. We argue that reasoning is crucial for understanding this broader class of offensive utterances and release SLIGHT, a dataset to support research on this task. Experiments using the data show that state-of-the-art methods of offense detection perform poorly when asked to detect implicitly offensive statements, achieving only ${\sim} 11\%$ accuracy. In contrast to existing offensive text detection datasets, SLIGHT features human-annotated chains of reasoning which describe the mental process by which an offensive interpretation can be reached from each ambiguous statement. We explore the potential for a multi-hop reasoning approach by utilizing existing entailment models to score the probability of these chains and show that even naive reasoning models can yield improved performance in most situations. Furthermore, ... : 18 pages, 4 figures, 10 tables, accepted in Findings of the Association for Computational Linguistics 2022 ... Keyword: Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences; Human-Computer Interaction cs.HC URL: https://dx.doi.org/10.48550/arxiv.2204.10521 https://arxiv.org/abs/2204.10521 BASE Hide details 4 Language Modeling for Morphologically Rich Languages: Character-Aware Modeling for Word-Level Prediction ... Gerz, Daniela; Vulić, Ivan; Ponti, Edoardo. - : Apollo - University of Cambridge Repository, 2018 BASE Show details 5 Language Modeling for Morphologically Rich Languages: Character-Aware Modeling for Word-Level Prediction Gerz, Daniela; Vulić, Ivan; Ponti, Edoardo. - : MIT Press - Journals, 2018. : Transactions of the Association for Computational Linguistics, 2018 BASE Show details 6 A Structured Variational Autoencoder for Contextual Morphological Inflection Naradowsky, Jason; Cotterell, Ryan; Mielke, Sebastian J. - : Association for Computational Linguistics, 2018. : Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2018 BASE Show details 7 Represent, Aggregate, and Constrain: A Novel Architecture for Machine Reading from Noisy Sources ... Naradowsky, Jason; Riedel, Sebastian. - : arXiv, 2016 BASE Show details 8 Learning with joint inference and latent linguistic structure in graphical models Naradowsky, Jason. - : Sydney, Australia : Macquarie University, 2015 BASE Show details 9 Grammarless parsing for joint inference Naradowsky, Jason; Vieira, Tim; Smith, David A. - : Mumbai, India : The COLING 2012 Organizing Committee, 2012 BASE Show details 10 Polylingual Topic Models Mimno, David; Wallach, Hanna M.; Naradowsky, Jason... In: Hanna M. Wallach (2009) BASE Show details 11 Polylingual Topic Models Mimno, David; Wallach, Hanna M.; Naradowsky, Jason... In: Andrew McCallum (2009) BASE Show details

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